Hyponatremia in the 2009 161-km Western States Endurance Run

Purpose:To determine the incidence of exercise-associated hyponatremia (EAH), the associated biochemical measurements and risk factors for EAH, and whether there is an association between postrace blood sodium concentration ([Na+]) and changes in body mass among participants in the 2009 Western States Endurance Run, a 161-km mountain trail run. Methods: Change in body mass, postrace [Na+], and blood creatine phosphokinase (CPK) concentration, and selected runner characteristics were evaluated among consenting competitors. Results: Of the 47 study participants, 14 (30%) had EAH as defined by a postrace [Na+] /L. Postrace [Na+] and percent change in body mass were directly related (r = .30, P = .044), and 50% of those with EAH had body mass losses of 3–6%. EAH was unrelated to age, sex, finish time, or use of nonsteroidal anti-inflammatory drugs during the run, but those with EAH had completed a smaller (P = .03) number of 161-km ultramarathons. The relationship of CPK levels to postrace [Na+] did not reach statistical significance (r = –.25, P = .097). Conclusions: EAH was common (30%) among finishers of this 161-km ultramarathon and it was not unusual for those with EAH to be dehydrated. As such, changes in body mass should not be relied upon in the assessment for EAH during 161-km ultramarathons

Dynamic Evolution of Permeability in Response to Chemo‐Mechanical Compaction

Pressure‐solution creep is an important fluid‐mediated deformation mechanism, causing chemo‐mechanical transformations and porosity and permeability changes in rocks. The presence of phyllosilicates, in particular, has previously been hypothesized to further reduce porosity and pore connectivity. Nevertheless, a full characterization of the spatio‐temporal evolution of permeability during this process has yet to be reported. A pure NaCl aggregate and a mixture of NaCl and biotite were deformed through pressure‐solution creep while monitoring their microstructural evolution through computed X‐ray micro‐tomography. The evolution of permeability and fluid velocity of the samples were computed by using the pore geometries from the X‐ray micro‐tomography as input for the Lattice‐Boltzmann modeling. The results indicate that, as deformation proceeds, porosity and permeability decrease in both samples. In the salt ‐biotite sample pressure solution creep causes the formation of a compaction band perpendicular to the direction of loading, forming a barrier for permeability. Along the other two directions, pore connectivity and permeability are retained in the marginal salt layers, making the sample strongly anisotropic. The presence of biotite controls the way pore coordination number evolves and hence, the connectivity of the pathways. Biotite flakes create an enhanced porosity decrease leading to compaction and reduction of pore connectivity. This reduction in porosity affects local stresses and local contact areas, reducing over time the driving force. According to a texture‐porosity process, the reduction in porosity causes salt ions to dissolve in the marginal salt and precipitate within the biotite‐bearing layer, where the bulk volume of salt grains increases over time

Severe Lumbar Disability Is Associated With Decreased Psoas Cross-Sectional Area in Degenerative Spondylolisthesis

Study Design: Retrospective cohort. Objectives: Alterations in lumbar paraspinal muscle cross-sectional area (CSA) may correlate with lumbar pathology. The purpose of this study was to compare paraspinal CSA in patients with degenerative spondylolisthesis and severe lumbar disability to those with mild or moderate lumbar disability, as determined by the Oswestry Disability Index (ODI). Methods: We retrospectively reviewed the medical records of 101 patients undergoing lumbar fusion for degenerative spondylolisthesis. Patients were divided into ODI score ≤40 (mild/moderate disability, MMD) and ODI score \u3e40 (severe disability, SD) groups. The total CSA of the psoas and paraspinal muscles were measured on preoperative magnetic resonance imaging (MRI). Results: There were 37 patients in the SD group and 64 in the MMD group. Average age and body mass index were similar between groups. For the paraspinal muscles, we were unable to demonstrate any significant differences in total CSA between the groups. Psoas muscle CSA was significantly decreased in the SD group compared with the MMD group (1010.08 vs 1178.6 mm2, P =.041). Multivariate analysis found that psoas CSA in the upper quartile was significantly protective against severe disability (P =.013). Conclusions: We found that patients with severe lumbar disability had no significant differences in posterior lumbar paraspinal CSA when compared with those with mild/moderate disability. However, severely disabled patients had significantly decreased psoas CSA, and larger psoas CSA was strongly protective against severe disability, suggestive of a potential association with psoas atrophy and worsening severity of lumbar pathology. © The Author(s) 2018

Search for nearby Earth analogs I. 15 planet candidates found in PFS data

30 pages, 20 figures, 3 tables, accepted for publication in ApJSThe radial velocity (RV) method plays a major role in the discovery of nearby exoplanets. To efficiently find planet candidates from the data obtained in high-precision RV surveys, we apply a signal diagnostic framework to detect RV signals that are statistically significant, consistent in time, robust in the choice of noise models, and do not correlated with stellar activity. Based on the application of this approach to the survey data of the Planet Finder Spectrograph, we report 15 planet candidates located in 14 stellar systems. We find that the orbits of the planet candidates around HD 210193, 103949, 8326, and 71135 are consistent with temperate zones around these stars (where liquid water could exist on the surface). With periods of 7.76 and 15.14 days, respectively, the planet candidates around star HIP 54373 form a 1:2 resonance system. These discoveries demonstrate the feasibility of automated detection of exoplanets from large RV surveys, which may provide a complete sample of nearby Earth analogs.Peer reviewedFinal Accepted Versio

A Six-Planet System Around the Star HD 34445

We present a new precision radial velocity dataset that reveals a multi-planet system orbiting the G0V star HD 34445. Our 18-year span consists of 333 precision radial velocity observations, 56 of which were previously published, and 277 which are new data from Keck Observatory, Magellan at Las Campanas Observatory, and the Automated Planet Finder at Lick Observatory. These data indicate the presence of six planet candidates in Keplerian motion about the host star with periods of 1057, 215, 118, 49, 677, and 5700 days, and minimum masses of 0.63, 0.17, 0.1, 0.05, 0.12 and 0.38 Jupiter masses respectively. The HD 34445 planetary system, with its high degree of multiplicity, its long orbital periods, and its induced stellar radial velocity half-amplitudes in the range $2 \,{\rm m\, s^{-1}} \lesssim K \lesssim 5\,{\rm m\, s^{-1}}$ is fundamentally unlike either our own solar system (in which only Jupiter and Saturn induce significant reflex velocities for the Sun), or the Kepler multiple-transiting systems (which tend to have much more compact orbital configurations)Comment: 10 pages, 11 figure

Using internal standards in time-resolved X-ray micro-computed tomography to quantify grain-scale developments in solid-state mineral reactions

X-ray computed tomography has established itself as a crucial tool in the analysis of rock materials, providing the ability to visualise intricate 3D microstructures and capture quantitative information about internal phenomena such as structural damage, mineral reactions, and fluid–rock interactions. The efficacy of this tool, however, depends significantly on the precision of image segmentation, a process that has seen varied results across different methodologies, ranging from simple histogram thresholding to more complex machine learning and deep-learning strategies. The irregularity in these segmentation outcomes raises concerns about the reproducibility of the results, a challenge that we aim to address in this work.In our study, we employ the mass balance of a metamorphic reaction as an internal standard to verify segmentation accuracy and shed light on the advantages of deep-learning approaches, particularly their capacity to efficiently process expansive datasets. Our methodology utilises deep learning to achieve accurate segmentation of time-resolved volumetric images of the gypsum dehydration reaction, a process that traditional segmentation techniques have struggled with due to poor contrast between reactants and products. We utilise a 2D U-net architecture for segmentation and introduce machine-learning-obtained labelled data (specifically, from random forest classification) as an innovative solution to the limitations of training data obtained from imaging. The deep-learning algorithm we developed has demonstrated remarkable resilience, consistently segmenting volume phases across all experiments. Furthermore, our trained neural network exhibits impressively short run times on a standard workstation equipped with a graphic processing unit (GPU). To evaluate the precision of our workflow, we compared the theoretical and measured molar evolution of gypsum to bassanite during dehydration. The errors between the predicted and segmented volumes in all time series experiments fell within the 2 % confidence intervals of the theoretical curves, affirming the accuracy of our methodology. We also compared the results obtained by the proposed method with standard segmentation methods and found a significant improvement in precision and accuracy of segmented volumes. This makes the segmented computed tomography images suited for extracting quantitative data, such as variations in mineral growth rate and pore size during the reaction.In this work, we introduce a distinctive approach by using an internal standard to validate the accuracy of a segmentation model, demonstrating its potential as a robust and reliable method for image segmentation in this field. This ability to measure the volumetric evolution during a reaction with precision paves the way for advanced modelling and verification of the physical properties of rock materials, particularly those involved in tectono-metamorphic processes. Our work underscores the promise of deep-learning approaches in elevating the quality and reproducibility of research in the geosciences